We used the trace gas model DayCent to simulate emissions of nitrous oxide (N2O) from a urine-affected pasture in New Zealand. The data set for this site contained year-round daily emissions of nitrification-N2O (N2Onit) and denitrification-N2O (N2Oden), meteorological data, soil moisture, and at least weekly data on soil ammonium (NH4+) and nitrate (NO3-) content. Evapotranspiration, soil temperature, and most of the soil moisture data were reasonably well represented. Observed and simulated soil NH4+ concentrations agreed well, but DayCent underestimated the NO3- concentrations, due possibly to an insufficient nitrification rate. Modeled N2O emissions (18.4 kg N2O-N ha-1 yr-1) showed a similar pattern but exceeded observed emissions (4.4 kg N2O-N ha-1 yr-1) by more than 3 times. Modeled and observed N2O emissions were dominated by peaks following N-application and heavy rainfall events and were favored under high soil temperatures. The contribution of N2Oden was simulated well except for a 4-week period when water-filled pore space was overestimated and caused high N2O emissions which accounted for one third of the simulated annual N2O emissions. N2Onit fluxes were overestimated with DayCent because they are calculated as a fixed proportion of NH4+ converted to NO3-, while the data suggest that significant rates of nitrification can occur without inducing significant N2O emissions. The comprehensive data set made it possible to explain discrepancies between modeled and observed values. In-depth model validations with detailed data sets are essential for a better understanding of the internal model behavior and for deriving possible model improvements.